Researchers at INKY observed a major phishing campaign that used SVG (Scalable Vector Graphics) image files to deliver malicious JavaScript. While abuse of SVG files isn’t new, INKY says their use in phishing campaigns has exploded over the past year.
With inboxes increasingly well guarded, cybercriminals are turning to a more vulnerable front in their attacks against your digital workforce.
Quantum Readiness Day on 24 September is a useful reminder that the security work we do today is not only about preventing breaches tomorrow. It is about protecting data and digital trust for years to come.
Researchers at Zimperium are tracking widespread phishing campaigns that use Browser-in-the-Browser (BitB) attacks to trick users into handing over their enterprise credentials. The attackers impersonate real HR employees at major companies and target job seekers with extremely realistic interview processes.
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A new phishing kit is using generative AI to fully automate voice phishing (vishing) attacks, according to researchers at Group-IB.
The phishing platform, called “Balonx,” includes a module dubbed “CallFlow” that the researchers say “represents a fundamental evolution” in the phishing-as-a-service market. This module uses four commercial AI services to conduct the attacks: OpenAI’s GPT-4o-mini, ElevenLabs’s AI voice generator, OpenAI Voice, and OpenAI Whisper.
When an organization has a security breach, it can cause significant financial, reputational and logistical damage. But in healthcare, where patient lives are on the line, the consequences can be much more catastrophic.
KnowBe4’s latest whitepaper on healthcare cybersecurity, “Hacking the Healers: How the Digital Workforce Became Cybersecurity's Frontline,” examines how decentralized clinical operations, remote staff and autonomous AI agents have dissolved traditional network perimeters, leaving healthcare organizations and patient safety vulnerable to targeted cyberattacks.
Cloaked SEO poisoning attacks surged by 40% in the second quarter of 2026, according to researchers at Fortra. This tactic, also known as “Chameleon SEO poisoning,” uses cloaked search engine results to spread phishing sites.
Threat actors’ abuse of enterprise collaboration tools increased fourfold over the past twelve months, according to researchers at Palo Alto Networks’ Unit 42.
Attackers are using “wrong-number” texts to identify potential targets for scams, according to researchers at Malwarebytes.
These texts appear to be harmless messages meant for another person, such as “Are we still on for dinner tomorrow?” or “Where’s the PowerPoint?” Recipients often try to be helpful by replying to let the person know they’ve got the wrong number. This reply, however, informs the threat actor that the phone number is active and marks it for future scams.
Attackers are distributing a new Android malware called “WindRelay” via phone-based social engineering attacks, according to researchers at Group-IB. The attackers call the victims, impersonating bank employees and instruct them to install a malicious app. In one instance observed by Group-IB, the scammers carried out the entire attack in just thirteen minutes.
A study has found that AI chatbots can be more effective at social engineering than human scammers, WIRED reports. The researchers looked at a form of romance scam commonly known as “pig butchering,” in which scammers spend weeks or months building a relationship with the victim before tricking them into sending money for a phony investment scheme.
Welcome back, cyberwarriors!
Earlier, we wrote an article on the issues that cars have. These issues are still common and car ransomware might soon emerge, hitting not just individual cars but entire fleets as vehicles get more autonomous and packed with different features.
In light of that, we want to show you a tool that makes car hacking more approachable. It’s GearGoat. The tool was built to simulate a car’s internal network so you can play with it.
GearGoat is a car simulator developed by INE Labs. It lets you work with the internal communication network used by most modern vehicles (CAN bus). Every action generates CAN packets on a virtual interface. You can use cansniffer, candump and UDS scanners with GearGoat, just like with any vehicle.
In a real car, you’d connect a CAN adapter (CANable or Macchina M2) into the OBD-II port, located under the dashboard. This port is basically a gateway into the vehicle’s internal network. Your system will treat the adapter as a network interface (can0) and you can start capturing and sending CAN messages. When someone presses the brake or turns on the indicators, it generates messages that travel across the network.
GearGoat runs inside a Docker container, so it’s easy to deploy. Clone the repository and run the script:
Login
kali > git clone https://github.com/ine-labs/GearGoat.git
kali > cd GearGoat
kali > sudo chmod +x initial_setup.sh
kali > sudo ./initial_setup.sh
Then you need to configure the virtual CAN interface (vcan0):
kali > sudo chmod +x vcan_setup.sh
kali > sudo ./vcan_setup.shOn certain distros you might be missing kernel modules. Here’s how you install them:
kali > sudo apt-get install -y linux-modules-extra-$(uname -r)It doesn’t always work on Kali Linux though. You can manually load the required modules and create the interface yourself:
kali > sudo modprobe vcan
kali > sudo ip link add dev vcan0 type vcan
kali > sudo ip link set up vcan0
kali > ip link show vcan0
Now everything should be ready. You can start GearGoat:
kali > sudo docker run --network="host" --privileged geargoat
The simulator will be hosted on http://localhost. There you’ll see different car functions. Each button on the interface generates CAN traffic.
While the simulator’s running, it continuously generates CAN traffic. To see this traffic, use cansniffer.
kali > cansniffer -c vcan0
The output can feel overwhelming. The tool keeps highlighting changing bytes dynamically. It’s very noisy when you’re trying to establish a baseline. You need a way to tell the tool what normal looks like. Press Shift + 3 + Enter multiple times and cansniffer will treat the current state as the baseline. It won’t highlight the background noise anymore, so you’ll only see the changes you make.
Once the baseline is set, you can start playing with the simulator. Click the Left Indicator button and you’ll notice a change in the CAN data.
The first byte of a frame changes and it’s tied to 0x188. That means this identifier controls the indicator state.
When you play with the speedometer, you’ll see a different pattern. The changes happen in the 4th and 5th bytes are associated with 0x244. The speed climbs gradually.
Repeat this with other controls and you’ll see how functions map on the CAN bus.
Now we know which messages control specific functions, so we can interact with them.
To control the indicators, we’ll send CAN frames using cansend:
kali > cansend vcan0 188#0100000000000000 # left
kali > cansend vcan0 188#0200000000000000 # right
These commands will turn on the left and right indicators. The CAN bus runs at high speed, so these changes can be hard to catch. We used the watch command to make it more visible:
kali > watch -n 0.1 "cansend vcan0 188#0200000000000000"Working with speed gets slightly more complex. Earlier, we found the address (0x244) and that specific bytes that control the value. To set a speed, we need to convert miles per hour into the format the CAN message expects.
To simulate a speed of 50 miles per hour you send:
kali > cansend vcan0 244#0000001F6F
You can see the simulator accelerating. Use the formula V = round(mph / 0.6213751 * 100) to calculate the value, then convert it into hexadecimal using big-endian.
You can also capture and replay traffic. That way you can record a sequence of actions and reproduce them.
To capture traffic, you use candump with logging:
kali > candump -l vcan0 
It’ll record the CAN messages into a log file. Once captured, you can replay it:
kali > canplayer -I <log_file_name>.logGearGoat can get you started with car hacking. You work with a simulated CAN bus to understand the communication patterns and message structure. It’s easy to set up and it’s not resource intensive, so it’ll run on pretty much any computer.
We also have our three-day Car Hacking training, showing you real attacks. It includes CAN protocol exploitation and the use of Software Defined Radio (SDR). There we show you how modern vehicles are actually compromised.
The post Automobile Hacking: Hacking with GearGoat first appeared on Hackers Arise.
As the Asia-Pacific and Japan (APJ) region continues its rapid digital acceleration, Guam stands at a unique strategic intersection. Serving as a critical hub for telecommunications, government services and regional defense, the island’s cybersecurity posture is no longer just a local concern, it is a cornerstone of regional stability.
Vietnam has emerged as a cornerstone of the global digital economy, but this rapid digitization has come with a significant surge in sophisticated cyber threats. As the country transitions into a more mature technological landscape, the methods used to protect its most critical asset, the workforce, must also evolve. We are witnessing a pivotal move away from traditional, checkbox in-person training toward modern, automated and AI-driven digital resilience.
“You’re gonna need a bigger boat.”
You cannot protect what you do not know exists.
An initial access broker for ransomware gangs is targeting organizations with voice phishing (vishing) attacks through Microsoft Teams, according to researchers at Zscaler’s ThreatLabz.
A survey from Trustmi found that most employees believe they’d be able to spot a social engineering attack, but those same employees still rely primarily on outdated guidance to spot red flags. Generative AI has given attackers the ability to craft extremely convincing, error-free phishing emails.
Attackers are getting smarter. AI is making social engineering more convincing, more personalized, and harder to spot than ever before. Training the digital workforce, employees and agents, to recognize threats is necessary, but even the most security-conscious users can still make a mistake at the moment of risk.
